Model comparison
Gemini 1.5 Pro (May 2024) vs Llama-3.3-70B-Instruct
Gemini 1.5 Pro (May 2024) is the stronger model overall, scoring 32.1 to 30.6 on the Noometry Index.
Last verified . 30 shared benchmarks.
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MetaSummary
- They share 30 benchmarks with published results for both. Gemini 1.5 Pro (May 2024) scores higher in 5 categories and Llama-3.3-70B-Instruct in 4 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in long context, where Gemini 1.5 Pro (May 2024) leads 39.8 to 26.4.
- The biggest single-benchmark swing is MATH Level 5: 70.4% for Gemini 1.5 Pro (May 2024) and 41.6% for Llama-3.3-70B-Instruct.
- Llama-3.3-70B-Instruct has downloadable open weights; the other is API-only.
Side by side
| Gemini 1.5 Pro (May 2024) | Llama-3.3-70B-Instruct | |
|---|---|---|
| Provider | Meta | |
| Noometry Index | 32.1 | 30.6 |
| Released | 2024-02-15 | 2024-12-06 |
| Weights | Proprietary | Open |
| Context window | — | 128K |
| Max output | — | 4K |
| Input $ / M tokens | — | $0.10 |
| Output $ / M tokens | — | $0.32 |
| Results tracked | 45 | 43 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Gemini 1.5 Pro (May 2024) leads
Gemini 1.5 Pro (May 2024): 34.2 (#241), Llama-3.3-70B-Instruct: 31.0 (#290)
| Benchmark | Gemini 1.5 Pro (May 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| WeirdML | 22.2% | 14.4% |
| BigCodeBench Instruct | 43.8% | 46.9% |
| LMArena Coding | 1294 | 1268 |
| BigCodeBench Complete | 57.5% | 57.5% |
| SciCode | — | 26% |
| LiveBench Coding | — | 36.6% |
| CadEval | 34% | — |
| HumanEval+ | 79.3% | — |
| MBPP+ | 74.6% | — |
Agentic & Tool Use Llama-3.3-70B-Instruct leads
Gemini 1.5 Pro (May 2024): 17.9 (#145), Llama-3.3-70B-Instruct: 25.8 (#105)
| Benchmark | Gemini 1.5 Pro (May 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| BALROG | 21% | 23% |
| Berkeley Function Calling Leaderboard | — | 31.9% |
| TheAgentCompany | 3.4% | — |
| Cybench | 7.5% | — |
Reasoning Llama-3.3-70B-Instruct leads
Gemini 1.5 Pro (May 2024): 12.3 (#338), Llama-3.3-70B-Instruct: 14.1 (#327)
| Benchmark | Gemini 1.5 Pro (May 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| SimpleBench | 27.1% | 19.9% |
| LMArena Hard Prompts | 1296 | 1257 |
| DTBench | 59% | 59.5% |
| Epoch Capabilities Index | 131.73 | 127.33 |
| ForecastBench | 58.4 | 58.6 |
| ARC-AGI-2 | 0.8% | — |
| CritPt | — | 0% |
| LiveBench Reasoning | — | 50.8% |
| LiveBench Data Analysis | — | 49.5% |
| LMCA | — | 17.5% |
| BIG-Bench Hard | 89.2% | — |
| LiveBench | — | 50.2% |
Math Gemini 1.5 Pro (May 2024) leads
Gemini 1.5 Pro (May 2024): 25.8 (#266), Llama-3.3-70B-Instruct: 15.3 (#298)
| Benchmark | Gemini 1.5 Pro (May 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 23.1% | 5.1% |
| LMArena Math | 1315 | 1267 |
| MATH Level 5 | 70.4% | 41.6% |
| Omni-MATH | 36.4% | — |
| LiveBench Math | — | 42.2% |
Knowledge Llama-3.3-70B-Instruct leads
Gemini 1.5 Pro (May 2024): 29.4 (#239), Llama-3.3-70B-Instruct: 30.6 (#226)
| Benchmark | Gemini 1.5 Pro (May 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| GPQA Diamond | 57.2% | 47.4% |
| Confabulations | 13.5% | 22.8% |
| LMArena Expert | 1279 | 1225 |
| MMLU | 86.9% | 86.3% |
| Humanity's Last Exam | 4.6% | — |
| MMLU-Pro | 73.7% | — |
| Vectara Hallucination Rate | — | 4.1% |
| GPQA (HELM) | 53.4% | — |
Multimodal Not comparable
Gemini 1.5 Pro (May 2024): 36.8 (#77), Llama-3.3-70B-Instruct: —
| Benchmark | Gemini 1.5 Pro (May 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Vision | 1161 | — |
| Video-MME | 75% | — |
Multilingual Gemini 1.5 Pro (May 2024) leads
Gemini 1.5 Pro (May 2024): 45.3 (#174), Llama-3.3-70B-Instruct: 39.9 (#220)
| Benchmark | Gemini 1.5 Pro (May 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Non-English | 1312 | 1236 |
| LMArena Chinese | 1331 | 1217 |
| LMArena French | 1302 | 1281 |
| LMArena German | 1286 | 1251 |
| LMArena Japanese | 1292 | 1150 |
| LMArena Korean | 1298 | 1143 |
| LMArena Russian | 1320 | 1252 |
| LMArena Spanish | 1311 | 1270 |
Instruction Following Llama-3.3-70B-Instruct leads
Gemini 1.5 Pro (May 2024): 68.6 (#185), Llama-3.3-70B-Instruct: 71.1 (#157)
| Benchmark | Gemini 1.5 Pro (May 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Instruction Following | 1297 | 1242 |
| LiveBench Instruction Following | — | 82.7% |
| IFEval | 83.7% | — |
Long Context Gemini 1.5 Pro (May 2024) leads
Gemini 1.5 Pro (May 2024): 39.8 (#169), Llama-3.3-70B-Instruct: 26.4 (#295)
| Benchmark | Gemini 1.5 Pro (May 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Longer Query | 1308 | 1256 |
| Fiction.LiveBench | — | 33.3% |
Writing & Preference Gemini 1.5 Pro (May 2024) leads
Gemini 1.5 Pro (May 2024): 52.4 (#172), Llama-3.3-70B-Instruct: 47.6 (#207)
| Benchmark | Gemini 1.5 Pro (May 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Text | 1319 | 1274 |
| LMArena Creative Writing | 1333 | 1250 |
| LMArena Multi-Turn | 1296 | 1280 |
| WildBench | 81.3% | — |
| LiveBench Language | — | 39.2% |
Frequently asked questions
Is Gemini 1.5 Pro (May 2024) better than Llama-3.3-70B-Instruct?
Gemini 1.5 Pro (May 2024) is the stronger model overall, scoring 32.1 to 30.6 on the Noometry Index.
Is Gemini 1.5 Pro (May 2024) or Llama-3.3-70B-Instruct better for coding?
Gemini 1.5 Pro (May 2024) scores higher on coding benchmarks: 34.2 versus 31.0 in the Noometry coding category.
How many benchmarks do Gemini 1.5 Pro (May 2024) and Llama-3.3-70B-Instruct share?
30 benchmarks have published results for both models. Gemini 1.5 Pro (May 2024) has 45 scored results on Noometry and Llama-3.3-70B-Instruct has 43.